Ship drift

from datetime import datetime
from opendrift.models.shipdrift import ShipDrift

o = ShipDrift(loglevel=20)

o.add_readers_from_list([
    'https://thredds.met.no/thredds/dodsC/cmems/topaz6/dataset-topaz6-arc-15min-3km-be.ncml',
    'https://thredds.met.no/thredds/dodsC/mepslatest/meps_lagged_6_h_latest_2_5km_latest.nc',
    'https://thredds.met.no/thredds/dodsC/cmems/mywavewam3km/dataset-wam-arctic-1hr3km-be.ncml'
    ])

14:16:31 INFO    opendrift:576: OpenDriftSimulation initialised (version 1.14.8 / v1.14.8-22-ged2e201)

Seed ship elements at defined position and time Note: beam/length ratio is larger than allowed, but is then clipped internally

o.seed_elements(lon=5.0, lat=63.0, radius=1000, number=1000,
                time=datetime.now(),
                length=80.0, beam=20.0, height=9.0, draft=4.0)

14:16:31 WARNING opendrift.models.shipdrift:180: Ratio of beam to length should be in range 0.12 to 0.18, given range is 0.25-0.25. Using border value.
14:16:31 INFO    opendrift.models.basemodel.environment:203: Adding a global landmask from GSHHG
14:16:35 INFO    opendrift.models.basemodel.environment:227: Fallback values will be used for the following variables which have no readers:
14:16:35 INFO    opendrift.models.basemodel.environment:230:    horizontal_diffusivity: 100.000000
14:16:35 INFO    opendrift.models.basemodel.environment:230:    sea_surface_wave_stokes_drift_x_velocity: 0.000000
14:16:35 INFO    opendrift.models.basemodel.environment:230:    sea_surface_wave_stokes_drift_y_velocity: 0.000000
14:16:35 INFO    opendrift.models.basemodel.environment:230:    sea_surface_wave_significant_height: 0.000000
14:16:35 INFO    opendrift.models.basemodel.environment:230:    sea_surface_wave_mean_period_from_variance_spectral_density_second_frequency_moment: 0.000000

Running model

o.run(steps=24, stop_on_error=True)

14:16:35 INFO    opendrift:1847: Storing previous values of element property lon because of condition (('general:coastline_action', 'in', ['stranding', 'previous']), 'or', ('general:seafloor_action', 'in', ['previous']))
14:16:35 INFO    opendrift:1847: Storing previous values of element property lat because of condition (('general:coastline_action', 'in', ['stranding', 'previous']), 'or', ('general:seafloor_action', 'in', ['previous']))
14:16:35 INFO    opendrift:955: Using existing reader for land_binary_mask to move elements to ocean
14:16:35 INFO    opendrift:986: All points are in ocean
14:16:35 INFO    opendrift:2144: 2026-03-03 14:16:31.428776 - step 1 of 24 - 1000 active elements (0 deactivated)
14:16:35 INFO    opendrift.readers:63: Opening file with xr.open_dataset
14:16:37 INFO    opendrift.readers.reader_netCDF_CF_generic:332: Detected dimensions: {'x': 'x', 'y': 'y', 'time': 'time'}
14:16:37 INFO    opendrift.readers:63: Opening file with xr.open_dataset
14:16:38 INFO    opendrift.readers.reader_netCDF_CF_generic:332: Detected dimensions: {'time': 'time', 'x': 'x', 'y': 'y'}
14:16:38 INFO    opendrift.readers:63: Opening file with xr.open_dataset
14:16:40 INFO    opendrift.readers.reader_netCDF_CF_generic:332: Detected dimensions: {'y': 'rlat', 'x': 'rlon', 'time': 'time'}
14:16:41 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
14:16:41 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
14:16:42 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
14:16:42 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
14:16:43 INFO    opendrift.models.shipdrift:310: Using Stokes drift direction as wave direction
14:16:43 INFO    opendrift:2144: 2026-03-03 15:16:31.428776 - step 2 of 24 - 1000 active elements (0 deactivated)
14:16:44 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
14:16:44 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
14:16:44 INFO    opendrift.models.shipdrift:310: Using Stokes drift direction as wave direction
14:16:44 INFO    opendrift:2144: 2026-03-03 16:16:31.428776 - step 3 of 24 - 1000 active elements (0 deactivated)
14:16:45 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
14:16:45 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
14:16:46 INFO    opendrift.models.shipdrift:310: Using Stokes drift direction as wave direction
14:16:46 INFO    opendrift:2144: 2026-03-03 17:16:31.428776 - step 4 of 24 - 1000 active elements (0 deactivated)
14:16:48 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
14:16:48 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
14:16:49 INFO    opendrift.models.shipdrift:310: Using Stokes drift direction as wave direction
14:16:49 INFO    opendrift:2144: 2026-03-03 18:16:31.428776 - step 5 of 24 - 1000 active elements (0 deactivated)
14:16:50 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
14:16:50 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
14:16:51 INFO    opendrift.models.shipdrift:310: Using Stokes drift direction as wave direction
14:16:51 INFO    opendrift:2144: 2026-03-03 19:16:31.428776 - step 6 of 24 - 1000 active elements (0 deactivated)
14:16:52 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
14:16:52 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
14:16:53 INFO    opendrift.models.shipdrift:310: Using Stokes drift direction as wave direction
14:16:53 INFO    opendrift:2144: 2026-03-03 20:16:31.428776 - step 7 of 24 - 1000 active elements (0 deactivated)
14:16:54 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
14:16:54 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
14:16:54 INFO    opendrift.models.shipdrift:310: Using Stokes drift direction as wave direction
14:16:54 INFO    opendrift:2144: 2026-03-03 21:16:31.428776 - step 8 of 24 - 1000 active elements (0 deactivated)
14:16:55 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
14:16:55 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
14:16:56 INFO    opendrift.models.shipdrift:310: Using Stokes drift direction as wave direction
14:16:56 INFO    opendrift:2144: 2026-03-03 22:16:31.428776 - step 9 of 24 - 1000 active elements (0 deactivated)
14:16:57 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
14:16:57 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
14:16:58 INFO    opendrift.models.shipdrift:310: Using Stokes drift direction as wave direction
14:16:58 INFO    opendrift:2144: 2026-03-03 23:16:31.428776 - step 10 of 24 - 1000 active elements (0 deactivated)
14:16:59 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
14:16:59 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
14:17:00 INFO    opendrift.models.shipdrift:310: Using Stokes drift direction as wave direction
14:17:00 INFO    opendrift:2144: 2026-03-04 00:16:31.428776 - step 11 of 24 - 1000 active elements (0 deactivated)
14:17:01 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
14:17:01 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
14:17:01 INFO    opendrift.models.shipdrift:310: Using Stokes drift direction as wave direction
14:17:01 INFO    opendrift:2144: 2026-03-04 01:16:31.428776 - step 12 of 24 - 1000 active elements (0 deactivated)
14:17:03 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
14:17:03 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
14:17:04 INFO    opendrift.models.shipdrift:310: Using Stokes drift direction as wave direction
14:17:04 INFO    opendrift:2144: 2026-03-04 02:16:31.428776 - step 13 of 24 - 1000 active elements (0 deactivated)
14:17:05 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
14:17:05 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
14:17:06 INFO    opendrift.models.shipdrift:310: Using Stokes drift direction as wave direction
14:17:06 INFO    opendrift:2144: 2026-03-04 03:16:31.428776 - step 14 of 24 - 1000 active elements (0 deactivated)
14:17:07 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
14:17:07 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
14:17:07 INFO    opendrift.models.shipdrift:310: Using Stokes drift direction as wave direction
14:17:07 INFO    opendrift:2144: 2026-03-04 04:16:31.428776 - step 15 of 24 - 1000 active elements (0 deactivated)
14:17:08 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
14:17:08 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
14:17:09 INFO    opendrift.models.shipdrift:310: Using Stokes drift direction as wave direction
14:17:09 INFO    opendrift:2144: 2026-03-04 05:16:31.428776 - step 16 of 24 - 1000 active elements (0 deactivated)
14:17:11 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
14:17:11 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
14:17:11 INFO    opendrift.models.shipdrift:310: Using Stokes drift direction as wave direction
14:17:11 INFO    opendrift:2144: 2026-03-04 06:16:31.428776 - step 17 of 24 - 1000 active elements (0 deactivated)
14:17:13 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
14:17:13 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
14:17:13 INFO    opendrift.models.shipdrift:310: Using Stokes drift direction as wave direction
14:17:13 INFO    opendrift:2144: 2026-03-04 07:16:31.428776 - step 18 of 24 - 1000 active elements (0 deactivated)
14:17:15 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
14:17:15 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
14:17:16 INFO    opendrift.models.shipdrift:310: Using Stokes drift direction as wave direction
14:17:16 INFO    opendrift:2144: 2026-03-04 08:16:31.428776 - step 19 of 24 - 1000 active elements (0 deactivated)
14:17:17 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
14:17:17 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
14:17:18 INFO    opendrift.models.shipdrift:310: Using Stokes drift direction as wave direction
14:17:18 INFO    opendrift:2144: 2026-03-04 09:16:31.428776 - step 20 of 24 - 1000 active elements (0 deactivated)
14:17:19 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
14:17:19 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
14:17:20 INFO    opendrift.models.shipdrift:310: Using Stokes drift direction as wave direction
14:17:20 INFO    opendrift:2144: 2026-03-04 10:16:31.428776 - step 21 of 24 - 1000 active elements (0 deactivated)
14:17:21 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
14:17:21 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
14:17:22 INFO    opendrift.models.shipdrift:310: Using Stokes drift direction as wave direction
14:17:22 INFO    opendrift:2144: 2026-03-04 11:16:31.428776 - step 22 of 24 - 1000 active elements (0 deactivated)
14:17:24 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
14:17:24 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
14:17:25 INFO    opendrift.models.shipdrift:310: Using Stokes drift direction as wave direction
14:17:25 INFO    opendrift:2144: 2026-03-04 12:16:31.428776 - step 23 of 24 - 1000 active elements (0 deactivated)
14:17:26 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
14:17:26 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
14:17:27 INFO    opendrift.models.shipdrift:310: Using Stokes drift direction as wave direction
14:17:27 INFO    opendrift:2144: 2026-03-04 13:16:31.428776 - step 24 of 24 - 1000 active elements (0 deactivated)
14:17:29 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
14:17:29 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
14:17:29 INFO    opendrift.models.shipdrift:310: Using Stokes drift direction as wave direction

<xarray.Dataset> Size: 3MB
Dimensions:                                                                              (
                                                                                          trajectory: 1000,
                                                                                          time: 25)
Coordinates:
  * trajectory                                                                           (trajectory) int64 8kB ...
  * time                                                                                 (time) datetime64[ns] 200B ...
Data variables: (12/25)
    status                                                                               (trajectory, time) float32 100kB ...
    moving                                                                               (trajectory, time) float32 100kB ...
    age_seconds                                                                          (trajectory, time) float32 100kB ...
    origin_marker                                                                        (trajectory, time) float32 100kB ...
    lon                                                                                  (trajectory, time) float32 100kB ...
    lat                                                                                  (trajectory, time) float32 100kB ...
    ...                                                                                   ...
    y_sea_water_velocity                                                                 (trajectory, time) float32 100kB ...
    horizontal_diffusivity                                                               (trajectory, time) float32 100kB ...
    sea_surface_wave_stokes_drift_x_velocity                                             (trajectory, time) float32 100kB ...
    sea_surface_wave_stokes_drift_y_velocity                                             (trajectory, time) float32 100kB ...
    sea_surface_wave_significant_height                                                  (trajectory, time) float32 100kB ...
    sea_surface_wave_mean_period_from_variance_spectral_density_second_frequency_moment  (trajectory, time) float32 100kB ...
Attributes: (12/99)
    Conventions:                                                             ...
    standard_name_vocabulary:                                                ...
    featureType:                                                             ...
    title:                                                                   ...
    summary:                                                                 ...
    keywords:                                                                ...
    ...                                                                                                               ...
    geospatial_lon_units:                                                    ...
    geospatial_lon_resolution:                                               ...
    runtime:                                                                 ...
    geospatial_vertical_min:                                                 ...
    geospatial_vertical_max:                                                 ...
    geospatial_vertical_positive:                                            ...

xarray.Dataset

• Dimensions:
  • trajectory: 1000
  • time: 25
• Coordinates: (2)
  • trajectory
    (trajectory)
    int64
    0 1 2 3 4 5 ... 995 996 997 998 999

    cf_role :

    trajectory_id

    dtype :

    <class 'numpy.int32'>

    array([  0,   1,   2, ..., 997, 998, 999], shape=(1000,))

  • time
    (time)
    datetime64[ns]
    2026-03-03T14:16:31.428776 ... 2...

    standard_name :

    time

    long_name :

    time

    dtype :

    <class 'numpy.float64'>

    array(['2026-03-03T14:16:31.428776000', '2026-03-03T15:16:31.428776000',
           '2026-03-03T16:16:31.428776000', '2026-03-03T17:16:31.428776000',
           '2026-03-03T18:16:31.428776000', '2026-03-03T19:16:31.428776000',
           '2026-03-03T20:16:31.428776000', '2026-03-03T21:16:31.428776000',
           '2026-03-03T22:16:31.428776000', '2026-03-03T23:16:31.428776000',
           '2026-03-04T00:16:31.428776000', '2026-03-04T01:16:31.428776000',
           '2026-03-04T02:16:31.428776000', '2026-03-04T03:16:31.428776000',
           '2026-03-04T04:16:31.428776000', '2026-03-04T05:16:31.428776000',
           '2026-03-04T06:16:31.428776000', '2026-03-04T07:16:31.428776000',
           '2026-03-04T08:16:31.428776000', '2026-03-04T09:16:31.428776000',
           '2026-03-04T10:16:31.428776000', '2026-03-04T11:16:31.428776000',
           '2026-03-04T12:16:31.428776000', '2026-03-04T13:16:31.428776000',
           '2026-03-04T14:16:31.428776000'], dtype='datetime64[ns]')

• Data variables: (25)
  • status
    (trajectory, time)
    float32
    0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0

    dtype :

    <class 'numpy.int32'>

    valid_range :

    [0 0]

    flag_values :

    [0]

    flag_meanings :

    active

    array([[0., 0., 0., ..., 0., 0., 0.],
           [0., 0., 0., ..., 0., 0., 0.],
           [0., 0., 0., ..., 0., 0., 0.],
           ...,
           [0., 0., 0., ..., 0., 0., 0.],
           [0., 0., 0., ..., 0., 0., 0.],
           [0., 0., 0., ..., 0., 0., 0.]], shape=(1000, 25), dtype=float32)

  • moving
    (trajectory, time)
    float32
    1.0 1.0 1.0 1.0 ... 1.0 1.0 1.0 1.0

    dtype :

    <class 'numpy.int32'>

    minval :

    1

    maxval :

    1

    array([[1., 1., 1., ..., 1., 1., 1.],
           [1., 1., 1., ..., 1., 1., 1.],
           [1., 1., 1., ..., 1., 1., 1.],
           ...,
           [1., 1., 1., ..., 1., 1., 1.],
           [1., 1., 1., ..., 1., 1., 1.],
           [1., 1., 1., ..., 1., 1., 1.]], shape=(1000, 25), dtype=float32)

  • age_seconds
    (trajectory, time)
    float32
    0.0 3.6e+03 ... 8.28e+04 8.64e+04

    dtype :

    <class 'numpy.float32'>

    units :

    s

    minval :

    0.0

    maxval :

    86400.0

    array([[    0.,  3600.,  7200., ..., 79200., 82800., 86400.],
           [    0.,  3600.,  7200., ..., 79200., 82800., 86400.],
           [    0.,  3600.,  7200., ..., 79200., 82800., 86400.],
           ...,
           [    0.,  3600.,  7200., ..., 79200., 82800., 86400.],
           [    0.,  3600.,  7200., ..., 79200., 82800., 86400.],
           [    0.,  3600.,  7200., ..., 79200., 82800., 86400.]],
          shape=(1000, 25), dtype=float32)

  • origin_marker
    (trajectory, time)
    float32
    0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0

    dtype :

    <class 'numpy.int32'>

    unit :

    description :

    An integer kept constant during the simulation. Different values may be used for different seedings, to separate elements during analysis. With GUI, only a single seeding is possible.

    flag_values :

    [0]

    flag_meanings :

    Seed_0

    minval :

    0

    maxval :

    0

    array([[0., 0., 0., ..., 0., 0., 0.],
           [0., 0., 0., ..., 0., 0., 0.],
           [0., 0., 0., ..., 0., 0., 0.],
           ...,
           [0., 0., 0., ..., 0., 0., 0.],
           [0., 0., 0., ..., 0., 0., 0.],
           [0., 0., 0., ..., 0., 0., 0.]], shape=(1000, 25), dtype=float32)

  • lon
    (trajectory, time)
    float32
    5.035 5.077 5.162 ... 6.267 6.303

    dtype :

    <class 'numpy.float32'>

    units :

    degrees_east

    standard_name :

    longitude

    long_name :

    longitude

    axis :

    X

    minval :

    4.9398756

    maxval :

    6.74908

    array([[5.0348186, 5.0767727, 5.1624436, ..., 6.1713953, 6.213656 ,
            6.2513742],
           [5.007899 , 5.0469537, 5.148627 , ..., 6.316402 , 6.3333716,
            6.309605 ],
           [5.0193124, 5.08284  , 5.156592 , ..., 6.3448315, 6.3873973,
            6.4308558],
           ...,
           [5.0018587, 5.0651574, 5.15179  , ..., 6.3799615, 6.4373064,
            6.475772 ],
           [4.9773602, 5.0199018, 5.0913453, ..., 6.1528296, 6.214842 ,
            6.289478 ],
           [4.9929357, 5.057788 , 5.131901 , ..., 6.25684  , 6.2666283,
            6.3030796]], shape=(1000, 25), dtype=float32)

  • lat
    (trajectory, time)
    float32
    63.0 63.03 63.03 ... 63.0 63.01

    dtype :

    <class 'numpy.float32'>

    units :

    degrees_north

    standard_name :

    latitude

    long_name :

    latitude

    axis :

    Y

    minval :

    62.880226

    maxval :

    63.289078

    array([[63.004982, 63.02587 , 63.03384 , ..., 63.17218 , 63.19997 ,
            63.20918 ],
           [63.008007, 63.0156  , 63.010757, ..., 62.977795, 62.993866,
            62.99779 ],
           [62.99621 , 63.00492 , 63.00019 , ..., 63.129406, 63.148964,
            63.163372],
           ...,
           [63.001423, 63.006077, 63.003727, ..., 63.07687 , 63.068928,
            63.07727 ],
           [62.989754, 63.011383, 63.022556, ..., 63.197372, 63.205822,
            63.229103],
           [62.98824 , 62.987537, 62.99271 , ..., 62.983772, 63.001408,
            63.00994 ]], shape=(1000, 25), dtype=float32)

  • z
    (trajectory, time)
    float32
    0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0

    dtype :

    <class 'numpy.float32'>

    units :

    m

    standard_name :

    z

    long_name :

    vertical position

    axis :

    Z

    positive :

    up

    minval :

    0.0

    maxval :

    0.0

    array([[0., 0., 0., ..., 0., 0., 0.],
           [0., 0., 0., ..., 0., 0., 0.],
           [0., 0., 0., ..., 0., 0., 0.],
           ...,
           [0., 0., 0., ..., 0., 0., 0.],
           [0., 0., 0., ..., 0., 0., 0.],
           [0., 0., 0., ..., 0., 0., 0.]], shape=(1000, 25), dtype=float32)

  • orientation
    (trajectory, time)
    float32
    0.0 0.0 0.0 0.0 ... 1.0 1.0 1.0 1.0

    dtype :

    <class 'numpy.uint8'>

    units :

    1

    minval :

    0

    maxval :

    1

    array([[0., 0., 0., ..., 0., 0., 0.],
           [1., 1., 1., ..., 1., 1., 1.],
           [0., 0., 0., ..., 0., 0., 0.],
           ...,
           [1., 1., 1., ..., 1., 1., 1.],
           [0., 0., 0., ..., 0., 0., 0.],
           [1., 1., 1., ..., 1., 1., 1.]], shape=(1000, 25), dtype=float32)

  • length
    (trajectory, time)
    float32
    80.0 80.0 80.0 ... 80.0 80.0 80.0

    dtype :

    <class 'numpy.float32'>

    units :

    m

    min :

    1

    max :

    500

    description :

    Length of ship

    level :

    1

    minval :

    80.0

    maxval :

    80.0

    array([[80., 80., 80., ..., 80., 80., 80.],
           [80., 80., 80., ..., 80., 80., 80.],
           [80., 80., 80., ..., 80., 80., 80.],
           ...,
           [80., 80., 80., ..., 80., 80., 80.],
           [80., 80., 80., ..., 80., 80., 80.],
           [80., 80., 80., ..., 80., 80., 80.]],
          shape=(1000, 25), dtype=float32)

  • height
    (trajectory, time)
    float32
    9.0 9.0 9.0 9.0 ... 9.0 9.0 9.0 9.0

    dtype :

    <class 'numpy.float32'>

    units :

    m

    min :

    1

    max :

    100

    description :

    Total height of ship (above and below waterline)

    level :

    1

    minval :

    9.0

    maxval :

    9.0

    array([[9., 9., 9., ..., 9., 9., 9.],
           [9., 9., 9., ..., 9., 9., 9.],
           [9., 9., 9., ..., 9., 9., 9.],
           ...,
           [9., 9., 9., ..., 9., 9., 9.],
           [9., 9., 9., ..., 9., 9., 9.],
           [9., 9., 9., ..., 9., 9., 9.]], shape=(1000, 25), dtype=float32)

  • draft
    (trajectory, time)
    float32
    4.0 4.0 4.0 4.0 ... 4.0 4.0 4.0 4.0

    dtype :

    <class 'numpy.float32'>

    units :

    m

    min :

    1

    max :

    30

    description :

    Draft of ship (depth below water)

    level :

    1

    minval :

    4.0

    maxval :

    4.0

    array([[4., 4., 4., ..., 4., 4., 4.],
           [4., 4., 4., ..., 4., 4., 4.],
           [4., 4., 4., ..., 4., 4., 4.],
           ...,
           [4., 4., 4., ..., 4., 4., 4.],
           [4., 4., 4., ..., 4., 4., 4.],
           [4., 4., 4., ..., 4., 4., 4.]], shape=(1000, 25), dtype=float32)

  • beam
    (trajectory, time)
    float32
    20.0 20.0 20.0 ... 20.0 20.0 20.0

    dtype :

    <class 'numpy.float32'>

    min :

    1

    max :

    70

    units :

    m

    description :

    Beam (width) of ship

    level :

    1

    minval :

    20.0

    maxval :

    20.0

    array([[20., 20., 20., ..., 20., 20., 20.],
           [20., 20., 20., ..., 20., 20., 20.],
           [20., 20., 20., ..., 20., 20., 20.],
           ...,
           [20., 20., 20., ..., 20., 20., 20.],
           [20., 20., 20., ..., 20., 20., 20.],
           [20., 20., 20., ..., 20., 20., 20.]],
          shape=(1000, 25), dtype=float32)

  • wind_drag_coeff
    (trajectory, time)
    float32
    0.815 0.815 0.815 ... 0.815 0.815

    dtype :

    <class 'numpy.float32'>

    units :

    1

    minval :

    0.815

    maxval :

    0.815

    array([[0.815, 0.815, 0.815, ..., 0.815, 0.815, 0.815],
           [0.815, 0.815, 0.815, ..., 0.815, 0.815, 0.815],
           [0.815, 0.815, 0.815, ..., 0.815, 0.815, 0.815],
           ...,
           [0.815, 0.815, 0.815, ..., 0.815, 0.815, 0.815],
           [0.815, 0.815, 0.815, ..., 0.815, 0.815, 0.815],
           [0.815, 0.815, 0.815, ..., 0.815, 0.815, 0.815]],
          shape=(1000, 25), dtype=float32)

  • water_drag_coeff
    (trajectory, time)
    float32
    1.32 1.32 1.32 ... 1.32 1.32 1.32

    dtype :

    <class 'numpy.float32'>

    units :

    1

    minval :

    1.32

    maxval :

    1.32

    array([[1.32, 1.32, 1.32, ..., 1.32, 1.32, 1.32],
           [1.32, 1.32, 1.32, ..., 1.32, 1.32, 1.32],
           [1.32, 1.32, 1.32, ..., 1.32, 1.32, 1.32],
           ...,
           [1.32, 1.32, 1.32, ..., 1.32, 1.32, 1.32],
           [1.32, 1.32, 1.32, ..., 1.32, 1.32, 1.32],
           [1.32, 1.32, 1.32, ..., 1.32, 1.32, 1.32]],
          shape=(1000, 25), dtype=float32)

  • jibeProbability
    (trajectory, time)
    float32
    0.04 0.04 0.04 ... 0.04 0.04 0.04

    dtype :

    <class 'numpy.float32'>

    units :

    1/h

    minval :

    0.04

    maxval :

    0.04

    array([[0.04, 0.04, 0.04, ..., 0.04, 0.04, 0.04],
           [0.04, 0.04, 0.04, ..., 0.04, 0.04, 0.04],
           [0.04, 0.04, 0.04, ..., 0.04, 0.04, 0.04],
           ...,
           [0.04, 0.04, 0.04, ..., 0.04, 0.04, 0.04],
           [0.04, 0.04, 0.04, ..., 0.04, 0.04, 0.04],
           [0.04, 0.04, 0.04, ..., 0.04, 0.04, 0.04]],
          shape=(1000, 25), dtype=float32)

  • x_wind
    (trajectory, time)
    float32
    15.36 15.83 16.05 ... 11.25 11.25

    minval :

    5.4784226

    maxval :

    18.233835

    array([[15.361126, 15.825572, 16.047924, ...,  9.845493, 10.812465,
            10.812465],
           [15.409452, 15.367789, 15.618831, ..., 10.733884, 11.935641,
            11.935641],
           [13.880144, 14.50303 , 14.988174, ...,  9.4133  ,  9.402391,
             9.402391],
           ...,
           [15.570688, 16.148722, 16.417082, ...,  9.219056,  9.459811,
             9.459811],
           [15.303735, 15.246632, 15.238516, ...,  8.979222,  9.302339,
             9.302339],
           [16.872889, 16.36401 , 16.192787, ..., 10.347605, 11.250317,
            11.250317]], shape=(1000, 25), dtype=float32)

  • y_wind
    (trajectory, time)
    float32
    2.466 1.651 1.141 ... 10.92 10.92

    minval :

    -1.3699135

    maxval :

    11.029203

    array([[ 2.4656    ,  1.6507078 ,  1.1408244 , ...,  9.437649  ,
            10.29239   , 10.29239   ],
           [ 1.4017668 ,  0.8100755 ,  0.8056621 , ...,  9.098346  ,
             9.869754  ,  9.869754  ],
           [ 2.5347292 ,  1.8044149 ,  0.49566475, ...,  7.631018  ,
             8.462949  ,  8.462949  ],
           ...,
           [ 2.8522196 ,  1.5998334 ,  0.401931  , ...,  8.551959  ,
             8.8492985 ,  8.8492985 ],
           [ 2.077167  ,  2.5221384 ,  1.5075184 , ...,  6.458156  ,
             8.4211855 ,  8.4211855 ],
           [ 2.9665961 ,  2.0806353 ,  0.54572695, ..., 10.017548  ,
            10.918624  , 10.918624  ]], shape=(1000, 25), dtype=float32)

  • land_binary_mask
    (trajectory, time)
    float32
    0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0

    minval :

    0.0

    maxval :

    0.0

    array([[0., 0., 0., ..., 0., 0., 0.],
           [0., 0., 0., ..., 0., 0., 0.],
           [0., 0., 0., ..., 0., 0., 0.],
           ...,
           [0., 0., 0., ..., 0., 0., 0.],
           [0., 0., 0., ..., 0., 0., 0.],
           [0., 0., 0., ..., 0., 0., 0.]], shape=(1000, 25), dtype=float32)

  • x_sea_water_velocity
    (trajectory, time)
    float32
    0.3643 0.4566 ... -0.076 -0.076

    minval :

    -0.09151466

    maxval :

    0.6375178

    array([[ 0.36426952,  0.4565681 ,  0.5641656 , ...,  0.24453849,
             0.29990298,  0.29990298],
           [ 0.35411143,  0.3964    ,  0.48814157, ..., -0.04685838,
            -0.08709236, -0.08709236],
           [ 0.3294748 ,  0.39800695,  0.46992248, ...,  0.2996977 ,
             0.32261577,  0.32261577],
           ...,
           [ 0.33195525,  0.38288012,  0.47344777, ...,  0.17020345,
             0.13819441,  0.13819441],
           [ 0.30114302,  0.36476016,  0.45389104, ...,  0.272888  ,
             0.3128658 ,  0.3128658 ],
           [ 0.3008271 ,  0.3266298 ,  0.42212257, ..., -0.04000393,
            -0.07599579, -0.07599579]], shape=(1000, 25), dtype=float32)

  • y_sea_water_velocity
    (trajectory, time)
    float32
    0.124 0.05317 ... 0.225 0.225

    minval :

    -0.23210134

    maxval :

    0.35165384

    array([[ 0.12396118,  0.05317045, -0.00137643, ...,  0.23343733,
             0.21236281,  0.21236281],
           [ 0.13707662,  0.0860566 ,  0.03948061, ...,  0.20411153,
             0.20936352,  0.20936352],
           [ 0.14148362,  0.08587757,  0.05354873, ...,  0.17778842,
             0.1364825 ,  0.1364825 ],
           ...,
           [ 0.14809316,  0.09147209,  0.04972093, ...,  0.1612222 ,
             0.06878275,  0.06878275],
           [ 0.15687685,  0.10860165,  0.04553627, ...,  0.21621585,
             0.2074044 ,  0.2074044 ],
           [ 0.15408607,  0.1122733 ,  0.07847626, ...,  0.20278151,
             0.22498344,  0.22498344]], shape=(1000, 25), dtype=float32)

  • horizontal_diffusivity
    (trajectory, time)
    float32
    100.0 100.0 100.0 ... 100.0 100.0

    minval :

    100.0

    maxval :

    100.0

    array([[100., 100., 100., ..., 100., 100., 100.],
           [100., 100., 100., ..., 100., 100., 100.],
           [100., 100., 100., ..., 100., 100., 100.],
           ...,
           [100., 100., 100., ..., 100., 100., 100.],
           [100., 100., 100., ..., 100., 100., 100.],
           [100., 100., 100., ..., 100., 100., 100.]],
          shape=(1000, 25), dtype=float32)

  • sea_surface_wave_stokes_drift_x_velocity
    (trajectory, time)
    float32
    0.3444 0.3698 ... 0.1795 0.1795

    minval :

    0.16905746

    maxval :

    0.41734955

    array([[0.34442014, 0.36981243, 0.38806438, ..., 0.19217879, 0.1952542 ,
            0.1952542 ],
           [0.34217125, 0.36905238, 0.3753875 , ..., 0.17990777, 0.17494968,
            0.17494968],
           [0.3390606 , 0.36822307, 0.37351802, ..., 0.19952291, 0.20680939,
            0.20680939],
           ...,
           [0.33956215, 0.36794952, 0.3739164 , ..., 0.19290455, 0.19750932,
            0.19750932],
           [0.3407943 , 0.36477402, 0.3748619 , ..., 0.19057326, 0.19555818,
            0.19555818],
           [0.3389861 , 0.3591686 , 0.36917794, ..., 0.18425591, 0.17949617,
            0.17949617]], shape=(1000, 25), dtype=float32)

  • sea_surface_wave_stokes_drift_y_velocity
    (trajectory, time)
    float32
    0.01312 0.00213 ... 0.1331 0.1331

    minval :

    -0.047492415

    maxval :

    0.14082795

    array([[ 0.01312018,  0.00213025, -0.01009252, ...,  0.10709094,
             0.1247183 ,  0.1247183 ],
           [ 0.01567404,  0.00282823, -0.00982293, ...,  0.11506573,
             0.12498323,  0.12498323],
           [ 0.01531529,  0.00231695, -0.00919431, ...,  0.10064358,
             0.11723769,  0.11723769],
           ...,
           [ 0.01684811,  0.00267963, -0.00939842, ...,  0.0992166 ,
             0.11133571,  0.11133571],
           [ 0.01898371,  0.00649878, -0.00959674, ...,  0.10257044,
             0.12395319,  0.12395319],
           [ 0.01806127,  0.0053624 , -0.00692596, ...,  0.11504713,
             0.13309854,  0.13309854]], shape=(1000, 25), dtype=float32)

  • sea_surface_wave_significant_height
    (trajectory, time)
    float32
    6.642 7.144 7.445 ... 4.027 4.027

    minval :

    3.6396675

    maxval :

    8.269087

    array([[6.641747 , 7.1440763, 7.445244 , ..., 3.9909968, 3.838554 ,
            3.838554 ],
           [6.672329 , 7.1476183, 7.4830947, ..., 4.1854296, 4.0395036,
            4.0395036],
           [6.649967 , 7.1049166, 7.467642 , ..., 3.8978724, 3.7652974,
            3.7652974],
           ...,
           [6.669432 , 7.1196623, 7.4777374, ..., 4.013471 , 3.887652 ,
            3.887652 ],
           [6.640893 , 7.168541 , 7.569066 , ..., 3.9520025, 3.8321033,
            3.8321033],
           [6.63687  , 7.1042747, 7.4892697, ..., 4.1433115, 4.0265484,
            4.0265484]], shape=(1000, 25), dtype=float32)

  • sea_surface_wave_mean_period_from_variance_spectral_density_second_frequency_moment
    (trajectory, time)
    float32
    8.068 8.327 8.482 ... 6.559 6.559

    minval :

    6.100598

    maxval :

    9.295856

    array([[8.068474 , 8.327141 , 8.482336 , ..., 6.554079 , 6.2956266,
            6.2956266],
           [8.104255 , 8.334017 , 8.558276 , ..., 6.8096166, 6.625897 ,
            6.625897 ],
           [8.102002 , 8.306641 , 8.555443 , ..., 6.488183 , 6.235438 ,
            6.235438 ],
           ...,
           [8.116014 , 8.31901  , 8.560171 , ..., 6.6280227, 6.4047685,
            6.4047685],
           [8.094381 , 8.37404  , 8.615254 , ..., 6.5381107, 6.288924 ,
            6.288924 ],
           [8.097799 , 8.353903 , 8.5915785, ..., 6.747443 , 6.5588284,
            6.5588284]], shape=(1000, 25), dtype=float32)

• Indexes: (2)
  • trajectory
    PandasIndex

    PandasIndex(Index([  0,   1,   2,   3,   4,   5,   6,   7,   8,   9,
           ...
           990, 991, 992, 993, 994, 995, 996, 997, 998, 999],
          dtype='int64', name='trajectory', length=1000))

  • time
    PandasIndex

    PandasIndex(DatetimeIndex(['2026-03-03 14:16:31.428776', '2026-03-03 15:16:31.428776',
                   '2026-03-03 16:16:31.428776', '2026-03-03 17:16:31.428776',
                   '2026-03-03 18:16:31.428776', '2026-03-03 19:16:31.428776',
                   '2026-03-03 20:16:31.428776', '2026-03-03 21:16:31.428776',
                   '2026-03-03 22:16:31.428776', '2026-03-03 23:16:31.428776',
                   '2026-03-04 00:16:31.428776', '2026-03-04 01:16:31.428776',
                   '2026-03-04 02:16:31.428776', '2026-03-04 03:16:31.428776',
                   '2026-03-04 04:16:31.428776', '2026-03-04 05:16:31.428776',
                   '2026-03-04 06:16:31.428776', '2026-03-04 07:16:31.428776',
                   '2026-03-04 08:16:31.428776', '2026-03-04 09:16:31.428776',
                   '2026-03-04 10:16:31.428776', '2026-03-04 11:16:31.428776',
                   '2026-03-04 12:16:31.428776', '2026-03-04 13:16:31.428776',
                   '2026-03-04 14:16:31.428776'],
                  dtype='datetime64[ns]', name='time', freq='h'))

• Attributes: (99)

  Conventions :

  CF-1.11, ACDD-1.3

  standard_name_vocabulary :

  CF Standard Name Table v85

  featureType :

  trajectory

  title :

  OpenDrift trajectory simulation

  summary :

  Output from simulation with OpenDrift framework

  keywords :

  trajectory, drift, lagrangian, simulation

  history :

  Created 2026-03-03 14:16:35.566693

  date_created :

  2026-03-03T14:16:35.566713

  source :

  Output from simulation with OpenDrift

  model_url :

  https://github.com/OpenDrift/opendrift

  opendrift_class :

  ShipDrift

  opendrift_module :

  opendrift.models.shipdrift

  readers :

  odict_keys(['LazyReader: https://thredds.met.no/thredds/dodsC/cmems/topaz6/dataset-topaz6-arc-15min-3km-be.ncml', 'LazyReader: https://thredds.met.no/thredds/dodsC/mepslatest/meps_lagged_6_h_latest_2_5km_latest.nc', 'LazyReader: https://thredds.met.no/thredds/dodsC/cmems/mywavewam3km/dataset-wam-arctic-1hr3km-be.ncml', 'global_landmask'])

  time_coverage_start :

  2026-03-03 14:16:31.428776

  time_step_calculation :

  1:00:00

  time_step_output :

  1:00:00

  config_environment:constant:x_wind :

  None

  config_environment:fallback:x_wind :

  None

  config_environment:constant:y_wind :

  None

  config_environment:fallback:y_wind :

  None

  config_environment:constant:land_binary_mask :

  None

  config_environment:fallback:land_binary_mask :

  None

  config_environment:constant:x_sea_water_velocity :

  None

  config_environment:fallback:x_sea_water_velocity :

  None

  config_environment:constant:y_sea_water_velocity :

  None

  config_environment:fallback:y_sea_water_velocity :

  None

  config_environment:constant:horizontal_diffusivity :

  None

  config_environment:fallback:horizontal_diffusivity :

  100

  config_environment:constant:sea_surface_wave_stokes_drift_x_velocity :

  None

  config_environment:fallback:sea_surface_wave_stokes_drift_x_velocity :

  0

  config_environment:constant:sea_surface_wave_stokes_drift_y_velocity :

  None

  config_environment:fallback:sea_surface_wave_stokes_drift_y_velocity :

  0

  config_environment:constant:sea_surface_wave_significant_height :

  None

  config_environment:fallback:sea_surface_wave_significant_height :

  0

  config_environment:constant:sea_surface_wave_mean_period_from_variance_spectral_density_second_frequency_moment :

  None

  config_environment:fallback:sea_surface_wave_mean_period_from_variance_spectral_density_second_frequency_moment :

  0

  config_general:use_auto_landmask :

  True

  config_drift:current_uncertainty :

  0

  config_drift:current_uncertainty_uniform :

  0

  config_drift:max_speed :

  2.0

  config_readers:max_number_of_fails :

  1

  config_general:simulation_name :

  config_general:coastline_action :

  stranding

  config_general:coastline_approximation_precision :

  0.001

  config_general:time_step_minutes :

  60

  config_general:time_step_output_minutes :

  None

  config_seed:ocean_only :

  True

  config_seed:number :

  1

  config_drift:max_age_seconds :

  None

  config_drift:advection_scheme :

  euler

  config_drift:horizontal_diffusivity :

  0

  config_drift:profiles_depth :

  50

  config_drift:wind_uncertainty :

  0

  config_drift:relative_wind :

  False

  config_drift:deactivate_north_of :

  None

  config_drift:deactivate_south_of :

  None

  config_drift:deactivate_east_of :

  None

  config_drift:deactivate_west_of :

  None

  config_seed:origin_marker :

  0

  config_seed:z :

  0

  config_seed:orientation :

  random

  config_seed:length :

  80

  config_seed:height :

  8

  config_seed:draft :

  4.0

  config_seed:beam :

  10

  config_seed:wind_drag_coeff :

  1

  config_seed:water_drag_coeff :

  1

  config_seed:jibeProbability :

  0.04

  opendrift_version :

  1.14.8

  seed_geojson :

  {"features": [], "type": "FeatureCollection"}

  simulation_time :

  2026-03-03 14:16:35.573101

  reader_x_wind :

  ['https://thredds.met.no/thredds/dodsC/mepslatest/meps_lagged_6_h_latest_2_5km_latest.nc']

  reader_y_wind :

  ['https://thredds.met.no/thredds/dodsC/mepslatest/meps_lagged_6_h_latest_2_5km_latest.nc']

  reader_land_binary_mask :

  ['global_landmask']

  reader_x_sea_water_velocity :

  ['https://thredds.met.no/thredds/dodsC/cmems/topaz6/dataset-topaz6-arc-15min-3km-be.ncml', 'https://thredds.met.no/thredds/dodsC/cmems/mywavewam3km/dataset-wam-arctic-1hr3km-be.ncml']

  reader_y_sea_water_velocity :

  ['https://thredds.met.no/thredds/dodsC/cmems/topaz6/dataset-topaz6-arc-15min-3km-be.ncml', 'https://thredds.met.no/thredds/dodsC/cmems/mywavewam3km/dataset-wam-arctic-1hr3km-be.ncml']

  reader_horizontal_diffusivity :

  100

  reader_sea_surface_wave_stokes_drift_x_velocity :

  ['https://thredds.met.no/thredds/dodsC/cmems/mywavewam3km/dataset-wam-arctic-1hr3km-be.ncml']

  reader_sea_surface_wave_stokes_drift_y_velocity :

  ['https://thredds.met.no/thredds/dodsC/cmems/mywavewam3km/dataset-wam-arctic-1hr3km-be.ncml']

  reader_sea_surface_wave_significant_height :

  ['https://thredds.met.no/thredds/dodsC/cmems/mywavewam3km/dataset-wam-arctic-1hr3km-be.ncml']

  reader_sea_surface_wave_mean_period_from_variance_spectral_density_second_frequency_moment :

  ['https://thredds.met.no/thredds/dodsC/cmems/mywavewam3km/dataset-wam-arctic-1hr3km-be.ncml']

  time_coverage_end :

  2026-03-04 14:16:31.428776

  time_coverage_duration :

  P1DT0H0M0S

  time_coverage_resolution :

  P0DT1H0M0S

  performance :

  -------------------- Reader performance: -------------------- global_landmask 0:00:00.0 total 0:00:00.0 preparing 0:00:00.0 reading 0:00:00.0 masking -------------------- https://thredds.met.no/thredds/dodsC/cmems/topaz6/dataset-topaz6-arc-15min-3km-be.ncml 0:00:16.5 total 0:00:00.0 preparing 0:00:16.4 reading 0:00:00.0 interpolation 0:00:00.0 interpolation_time 0:00:00.0 rotating vectors 0:00:00.0 masking -------------------- https://thredds.met.no/thredds/dodsC/mepslatest/meps_lagged_6_h_latest_2_5km_latest.nc 0:00:17.0 total 0:00:00.0 preparing 0:00:16.9 reading 0:00:00.2 interpolation 0:00:00.0 interpolation_time 0:00:00.0 rotating vectors 0:00:00.0 masking -------------------- https://thredds.met.no/thredds/dodsC/cmems/mywavewam3km/dataset-wam-arctic-1hr3km-be.ncml 0:00:14.3 total 0:00:00.0 preparing 0:00:14.3 reading 0:00:00.0 interpolation 0:00:00.0 interpolation_time 0:00:00.0 rotating vectors 0:00:00.0 masking -------------------- Performance: 58.3 total time 4.1 configuration 0.0 preparing main loop 0.0 moving elements to ocean 54.2 main loop 0.5 updating elements 0.0 cleaning up --------------------

  geospatial_bounds_crs :

  EPSG:4326

  geospatial_bounds_vertical_crs :

  EPSG:5831

  geospatial_lat_min :

  62.880226

  geospatial_lat_max :

  63.289078

  geospatial_lat_units :

  degrees_north

  geospatial_lat_resolution :

  point

  geospatial_lon_min :

  4.9398756

  geospatial_lon_max :

  6.74908

  geospatial_lon_units :

  degrees_east

  geospatial_lon_resolution :

  point

  runtime :

  0:00:58.396774

  geospatial_vertical_min :

  0.0

  geospatial_vertical_max :

  0.0

  geospatial_vertical_positive :

  up

Print and plot results

print(o)
o.plot(linecolor='orientation')
#o.animation(color='orientation', markersize=20, filename="orientation.gif", legend=['left','right'],colorbar=False,cmap='bwr')
o.animation(color='orientation', legend=['left','right'], markersize=20, colorbar=False, cmap='bwr')

===========================
--------------------
Reader performance:
--------------------
global_landmask
 0:00:00.0  total
 0:00:00.0  preparing
 0:00:00.0  reading
 0:00:00.0  masking
--------------------
https://thredds.met.no/thredds/dodsC/cmems/topaz6/dataset-topaz6-arc-15min-3km-be.ncml
 0:00:16.5  total
 0:00:00.0  preparing
 0:00:16.4  reading
 0:00:00.0  interpolation
 0:00:00.0  interpolation_time
 0:00:00.0  rotating vectors
 0:00:00.0  masking
--------------------
https://thredds.met.no/thredds/dodsC/mepslatest/meps_lagged_6_h_latest_2_5km_latest.nc
 0:00:17.0  total
 0:00:00.0  preparing
 0:00:16.9  reading
 0:00:00.2  interpolation
 0:00:00.0  interpolation_time
 0:00:00.0  rotating vectors
 0:00:00.0  masking
--------------------
https://thredds.met.no/thredds/dodsC/cmems/mywavewam3km/dataset-wam-arctic-1hr3km-be.ncml
 0:00:14.3  total
 0:00:00.0  preparing
 0:00:14.3  reading
 0:00:00.0  interpolation
 0:00:00.0  interpolation_time
 0:00:00.0  rotating vectors
 0:00:00.0  masking
--------------------
Performance:
   58.3 total time
    4.1 configuration
    0.0 preparing main loop
      0.0 moving elements to ocean
   54.2 main loop
      0.5 updating elements
    0.0 cleaning up
--------------------
===========================
Model:  ShipDrift     (OpenDrift version 1.14.8)
        1000 active ShipObject particles  (0 deactivated, 0 scheduled)
-------------------
Environment variables:
  -----
  land_binary_mask
     1) global_landmask
  -----
  x_sea_water_velocity
  y_sea_water_velocity
     1) https://thredds.met.no/thredds/dodsC/cmems/topaz6/dataset-topaz6-arc-15min-3km-be.ncml
     2) https://thredds.met.no/thredds/dodsC/cmems/mywavewam3km/dataset-wam-arctic-1hr3km-be.ncml
  -----
  x_wind
  y_wind
     1) https://thredds.met.no/thredds/dodsC/mepslatest/meps_lagged_6_h_latest_2_5km_latest.nc
  -----
  sea_surface_wave_mean_period_from_variance_spectral_density_second_frequency_moment
  sea_surface_wave_significant_height
  sea_surface_wave_stokes_drift_x_velocity
  sea_surface_wave_stokes_drift_y_velocity
     1) https://thredds.met.no/thredds/dodsC/cmems/mywavewam3km/dataset-wam-arctic-1hr3km-be.ncml
  -----
Readers not added for the following variables:
  horizontal_diffusivity

Discarded readers:

Time:
        Start: 2026-03-03 14:16:31.428776 UTC
        Present: 2026-03-04 14:16:31.428776 UTC
        Calculation steps: 24 * 1:00:00 - total time: 1 day, 0:00:00
        Output steps: 25 * 1:00:00
===========================

14:17:53 INFO    opendrift:4705: Saving animation to /root/project/docs/source/gallery/animations/example_shipdrift_0.gif...
14:18:06 INFO    opendrift:3128: Time to make animation: 0:00:14.202183